{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/classification-1/papers/69","list_of":"/task/classification-1","task":"Classification","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":69,"pages_in_order":129,"rows_per_page":100,"rows":[6801,6900],"of":12815,"counts":{"archive_papers_tagged":12815,"with_a_code_link":3778,"where_syntology_ran_a_sample":582,"not_listed_spam_title":0,"listed":12815,"listed_where_code_ran":582,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":457,"every_run_a_failure_of_syntologys_instrument":125,"listed_with_a_run_with_no_instrument_failure":457,"listed_every_run_a_failure_of_syntologys_instrument":125,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/classification-1","prev":"/task/classification-1/papers/68","next":"/task/classification-1/papers/70","papers":[{"url":null,"slug":"aerial-scene-parsing-from-tile-level-scene","title":"Aerial Scene Parsing: From Tile-level Scene Classification to Pixel-wise Semantic Labeling","date":"2022-01-06","arxiv_id":"2201.01953","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-classification-system-for","title":"Deep Learning Based Classification System For Recognizing Local Spinach","date":"2022-01-06","arxiv_id":"2201.02093","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-label-classification-on-remote-sensing","title":"Multi-Label Classification on Remote-Sensing Images","date":"2022-01-06","arxiv_id":"2201.01971","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-investigation-of-ben-ford-s-law-divergence","title":"An Investigation of \"Benford's\" Law Divergence and Machine Learning Techniques for \"Intra-Class\" Separability of Fingerprint Images","date":"2022-01-05","arxiv_id":"2201.01699","repositories_listed":0,"syntology":null},{"url":null,"slug":"including-stdp-to-eligibility-propagation-in","title":"Including STDP to eligibility propagation in multi-layer recurrent spiking neural networks","date":"2022-01-05","arxiv_id":"2201.07602","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-the-classification-of","title":"Machine-Learning the Classification of Spacetimes","date":"2022-01-05","arxiv_id":"2201.01644","repositories_listed":0,"syntology":null},{"url":null,"slug":"problem-dependent-attention-and-effort-in","title":"Problem-dependent attention and effort in neural networks with applications to image resolution and model selection","date":"2022-01-05","arxiv_id":"2201.01415","repositories_listed":0,"syntology":null},{"url":null,"slug":"underwater-object-classification-and","title":"Underwater Object Classification and Detection: first results and open challenges","date":"2022-01-04","arxiv_id":"2201.00977","repositories_listed":0,"syntology":null},{"url":null,"slug":"zeroberto-leveraging-zero-shot-text","title":"ZeroBERTo: Leveraging Zero-Shot Text Classification by Topic Modeling","date":"2022-01-04","arxiv_id":"2201.01337","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-taxonomy-of-non-dictatorial-unidimensional","title":"A Taxonomy of Non-dictatorial Unidimensional Domains","date":"2022-01-03","arxiv_id":"2201.00496","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-template-enhancement-for-improved","title":"Adaptive Template Enhancement for Improved Person Recognition using Small Datasets","date":"2022-01-03","arxiv_id":"2201.01218","repositories_listed":0,"syntology":null},{"url":null,"slug":"riemannian-nearest-regularized-subspace","title":"Riemannian Nearest-Regularized Subspace Classification for Polarimetric SAR images","date":"2022-01-02","arxiv_id":"2201.00337","repositories_listed":0,"syntology":null},{"url":null,"slug":"destr-object-detection-with-split-transformer","title":"DESTR: Object Detection With Split Transformer","date":"2022-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"etude-de-classification-des-bacteriophages","title":"Etude de classification des bacteriophages","date":"2022-01-01","arxiv_id":"2201.00126","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-adversarially-robust-few-shot-image","title":"Improving Adversarially Robust Few-Shot Image Classification With Generalizable Representations","date":"2022-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"benign-overfitting-in-adversarially-robust-1","title":"Benign Overfitting in Adversarially Robust Linear Classification","date":"2021-12-31","arxiv_id":"2112.15250","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-with-category-attention","title":"Domain Adaptation with Category Attention Network for Deep Sentiment Analysis","date":"2021-12-31","arxiv_id":"2112.15290","repositories_listed":0,"syntology":null},{"url":null,"slug":"does-qa-based-intermediate-training-help-fine","title":"Does QA-based intermediate training help fine-tuning language models for text classification?","date":"2021-12-30","arxiv_id":"2112.15051","repositories_listed":0,"syntology":null},{"url":null,"slug":"ensemble-classification-of-anomalous","title":"Boosting the performance of anomalous diffusion classifiers with the proper choice of features","date":"2021-12-30","arxiv_id":"2112.15143","repositories_listed":0,"syntology":null},{"url":null,"slug":"rheframedetect-a-text-classification-system","title":"RheFrameDetect: A Text Classification System for Automatic Detection of Rhetorical Frames in AI from Open Sources","date":"2021-12-30","arxiv_id":"2112.14933","repositories_listed":0,"syntology":null},{"url":null,"slug":"textrgnn-residual-graph-neural-networks-for","title":"TextRGNN: Residual Graph Neural Networks for Text Classification","date":"2021-12-30","arxiv_id":"2112.15060","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-samme-c2-algorithm-for-severely","title":"The SAMME.C2 algorithm for severely imbalanced multi-class classification","date":"2021-12-30","arxiv_id":"2112.14868","repositories_listed":0,"syntology":null},{"url":null,"slug":"2112-14644","title":"Implementation of Convolutional Neural Network Architecture on 3D Multiparametric Magnetic Resonance Imaging for Prostate Cancer Diagnosis","date":"2021-12-29","arxiv_id":"2112.14644","repositories_listed":0,"syntology":null},{"url":null,"slug":"universal-online-learning-with-bounded-loss","title":"Universal Online Learning with Bounded Loss: Reduction to Binary Classification","date":"2021-12-29","arxiv_id":"2112.14638","repositories_listed":0,"syntology":null},{"url":null,"slug":"brain-tumor-classification-by-cascaded","title":"Brain Tumor Classification by Cascaded Multiscale Multitask Learning Framework Based on Feature Aggregation","date":"2021-12-28","arxiv_id":"2112.14320","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepadversaries-examining-the-robustness-of","title":"DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification","date":"2021-12-28","arxiv_id":"2112.14299","repositories_listed":0,"syntology":null},{"url":null,"slug":"source-feature-compression-for-object","title":"Source Feature Compression for Object Classification in Vision-Based Underwater Robotics","date":"2021-12-28","arxiv_id":"2112.13953","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-fistful-of-words-learning-transferable","title":"A Fistful of Words: Learning Transferable Visual Models from Bag-of-Words Supervision","date":"2021-12-27","arxiv_id":"2112.13884","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-channel-training-method-boost-the","title":"A Multi-channel Training Method Boost the Performance","date":"2021-12-27","arxiv_id":"2112.13727","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-eeg-based-approach-for-parkinson-s-disease","title":"An EEG-based approach for Parkinson's disease diagnosis using Capsule network","date":"2021-12-27","arxiv_id":"2201.00628","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-classification-in-unseen-domains-by","title":"Few-Shot Classification in Unseen Domains by Episodic Meta-Learning Across Visual Domains","date":"2021-12-27","arxiv_id":"2112.13539","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-normalized-classification-of-parkinson-s","title":"Self-normalized Classification of Parkinson's Disease DaTscan Images","date":"2021-12-27","arxiv_id":"2112.13637","repositories_listed":0,"syntology":null},{"url":null,"slug":"vir-the-vision-reservoir","title":"ViR:the Vision Reservoir","date":"2021-12-27","arxiv_id":"2112.13545","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-curriculum-learning-for-polsar-image","title":"Deep Curriculum Learning for PolSAR Image Classification","date":"2021-12-26","arxiv_id":"2112.13426","repositories_listed":0,"syntology":null},{"url":null,"slug":"prevalence-threshold-and-bounds-in-the","title":"Prevalence Threshold and bounds in the Accuracy of Binary Classification Systems","date":"2021-12-25","arxiv_id":"2112.13289","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-clustering-based-deduction-learning","title":"Semantic Clustering based Deduction Learning for Image Recognition and Classification","date":"2021-12-25","arxiv_id":"2112.13165","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-aligned-cross-modal-representation","title":"Learning Aligned Cross-Modal Representation for Generalized Zero-Shot Classification","date":"2021-12-24","arxiv_id":"2112.12927","repositories_listed":0,"syntology":null},{"url":null,"slug":"bi-directional-recurrent-neural-ordinary","title":"Bi-Directional Recurrent Neural Ordinary Differential Equations for Social Media Text Classification","date":"2021-12-23","arxiv_id":"2112.12809","repositories_listed":0,"syntology":null},{"url":null,"slug":"kfwc-a-knowledge-driven-deep-learning-model","title":"KFWC: A Knowledge-Driven Deep Learning Model for Fine-grained Classification of Wet-AMD","date":"2021-12-23","arxiv_id":"2112.12386","repositories_listed":0,"syntology":null},{"url":null,"slug":"prolog-based-agnostic-explanation-module-for","title":"Prolog-based agnostic explanation module for structured pattern classification","date":"2021-12-23","arxiv_id":"2112.12641","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-softmax-a-simpler-and-faster","title":"Sparse-softmax: A Simpler and Faster Alternative Softmax Transformation","date":"2021-12-23","arxiv_id":"2112.12433","repositories_listed":0,"syntology":null},{"url":null,"slug":"temporal-analysis-of-functional-brain","title":"Temporal Analysis of Functional Brain Connectivity for EEG-based Emotion Recognition","date":"2021-12-23","arxiv_id":"2112.12380","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-analysis-of-memes-for-sentiment","title":"Multimodal Analysis of memes for sentiment extraction","date":"2021-12-22","arxiv_id":"2112.11850","repositories_listed":0,"syntology":null},{"url":null,"slug":"augmented-contrastive-self-supervised","title":"Augmented Contrastive Self-Supervised Learning for Audio Invariant Representations","date":"2021-12-21","arxiv_id":"2112.10950","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-graph-contrastive-pretraining-for","title":"Supervised Graph Contrastive Pretraining for Text Classification","date":"2021-12-21","arxiv_id":"2112.11389","repositories_listed":0,"syntology":null},{"url":null,"slug":"task-oriented-image-transmission-for-scene","title":"Task-Oriented Image Transmission for Scene Classification in Unmanned Aerial Systems","date":"2021-12-21","arxiv_id":"2112.10948","repositories_listed":0,"syntology":null},{"url":null,"slug":"object-recognition-as-classification-of","title":"Object Recognition as Classification via Visual Properties","date":"2021-12-20","arxiv_id":"2112.10531","repositories_listed":0,"syntology":null},{"url":null,"slug":"skin-lesion-segmentation-and-classification-3","title":"Skin lesion segmentation and classification using deep learning and handcrafted features","date":"2021-12-20","arxiv_id":"2112.10307","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-augmentation-for-mental-health","title":"Data Augmentation for Mental Health Classification on Social Media","date":"2021-12-19","arxiv_id":"2112.10064","repositories_listed":0,"syntology":null},{"url":null,"slug":"sub-100uw-multispectral-riemannian","title":"Sub-100uW Multispectral Riemannian Classification for EEG-based Brain--Machine Interfaces","date":"2021-12-18","arxiv_id":"2112.10026","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparative-analysis-of-radar-cross-section","title":"Comparative Analysis of Radar Cross Section Based UAV Classification Techniques","date":"2021-12-17","arxiv_id":"2112.09774","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-learning-for-fair-representations-1","title":"Contrastive Learning for Fair Representations","date":"2021-12-17","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"overview-of-the-hasoc-subtrack-at-fire-2021","title":"Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages","date":"2021-12-17","arxiv_id":"2112.09301","repositories_listed":0,"syntology":null},{"url":null,"slug":"rank4class-a-ranking-formulation-for","title":"Rank4Class: A Ranking Formulation for Multiclass Classification","date":"2021-12-17","arxiv_id":"2112.09727","repositories_listed":0,"syntology":null},{"url":null,"slug":"alp-data-augmentation-using-lexicalized-pcfgs","title":"ALP: Data Augmentation using Lexicalized PCFGs for Few-Shot Text Classification","date":"2021-12-16","arxiv_id":"2112.11916","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmarking-uncertainty-quantification-on","title":"Benchmarking Uncertainty Quantification on Biosignal Classification Tasks under Dataset Shift","date":"2021-12-16","arxiv_id":"2112.09196","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-under-ambiguity-when-is","title":"Classification Under Ambiguity: When Is Average-K Better Than Top-K?","date":"2021-12-16","arxiv_id":"2112.08851","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiple-instance-learning-for-brain-tumor","title":"Multiple Instance Learning for Brain Tumor Detection from Magnetic Resonance Spectroscopy Data","date":"2021-12-16","arxiv_id":"2112.08845","repositories_listed":0,"syntology":null},{"url":null,"slug":"covid-19-electrocardiograms-classification","title":"COVID-19 Electrocardiograms Classification using CNN Models","date":"2021-12-15","arxiv_id":"2112.08931","repositories_listed":0,"syntology":null},{"url":null,"slug":"mask-combine-decoding-and-classification","title":"Mask-combine Decoding and Classification Approach for Punctuation Prediction with real-time Inference Constraints","date":"2021-12-15","arxiv_id":"2112.08098","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-neural-network-classification-via","title":"Robust Neural Network Classification via Double Regularization","date":"2021-12-15","arxiv_id":"2112.08102","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-of-histopathology-images-using","title":"Classification of histopathology images using ConvNets to detect Lupus Nephritis","date":"2021-12-14","arxiv_id":"2112.07555","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-category-correlated-feature-for-few","title":"Exploring Category-correlated Feature for Few-shot Image Classification","date":"2021-12-14","arxiv_id":"2112.07224","repositories_listed":0,"syntology":null},{"url":null,"slug":"neighborhood-random-walk-graph-sampling-for","title":"Neighborhood Random Walk Graph Sampling for Regularized Bayesian Graph Convolutional Neural Networks","date":"2021-12-14","arxiv_id":"2112.07743","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-automatic-transformer-based-cloud","title":"Towards Automatic Transformer-based Cloud Classification and Segmentation","date":"2021-12-14","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-of-toxic-comment-classification","title":"A Survey of Toxic Comment Classification Methods","date":"2021-12-13","arxiv_id":"2112.06412","repositories_listed":0,"syntology":null},{"url":null,"slug":"accelerating-deep-learning-classification","title":"Accelerating Deep Learning Classification with Error-controlled Approximate-key Caching","date":"2021-12-13","arxiv_id":"2112.06671","repositories_listed":0,"syntology":null},{"url":"/paper/decoupling-object-detection-from-human-object-1","slug":"decoupling-object-detection-from-human-object-1","title":"The Overlooked Classifier in Human-Object Interaction Recognition","date":"2021-12-13","arxiv_id":"2112.06392","repositories_listed":0,"syntology":null},{"url":null,"slug":"khmer-text-classification-using-word","title":"Khmer Text Classification Using Word Embedding and Neural Networks","date":"2021-12-13","arxiv_id":"2112.06748","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-nigerian-accent-embeddings-from","title":"Learning Nigerian accent embeddings from speech: preliminary results based on SautiDB-Naija corpus","date":"2021-12-12","arxiv_id":"2112.06199","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-attention-multiple-instance-learning","title":"Multi-Attention Multiple Instance Learning","date":"2021-12-11","arxiv_id":"2112.06071","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-hardware-system-for-cascade-svm","title":"Dynamic hardware system for cascade SVM classification of melanoma","date":"2021-12-10","arxiv_id":"2112.05322","repositories_listed":0,"syntology":null},{"url":null,"slug":"mathematical-models-of-covid-19-spread","title":"Mathematical models of COVID-19 spread","date":"2021-12-10","arxiv_id":"2112.05315","repositories_listed":0,"syntology":null},{"url":null,"slug":"amicable-aid-turning-adversarial-attack-to","title":"Amicable Aid: Perturbing Images to Improve Classification Performance","date":"2021-12-09","arxiv_id":"2112.04720","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-of-anuran-frog-species-using","title":"Classification of Anuran Frog Species Using Machine Learning","date":"2021-12-09","arxiv_id":"2112.05148","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-multivariate-randomized-classification","title":"On multivariate randomized classification trees: $l_0$-based sparsity, VC~dimension and decomposition methods","date":"2021-12-09","arxiv_id":"2112.05239","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-effect-of-coding-artifacts-on-acoustic","title":"On The Effect Of Coding Artifacts On Acoustic Scene Classification","date":"2021-12-09","arxiv_id":"2112.04841","repositories_listed":0,"syntology":null},{"url":null,"slug":"merging-subject-matter-expertise-and-deep","title":"Merging Subject Matter Expertise and Deep Convolutional Neural Network for State-Based Online Machine-Part Interaction Classification","date":"2021-12-08","arxiv_id":"2112.04572","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-generic-auto-ml-tools-for","title":"Evaluating Generic Auto-ML Tools for Computational Pathology","date":"2021-12-07","arxiv_id":"2112.03622","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-image-classification-along-sparse","title":"Few-Shot Image Classification Along Sparse Graphs","date":"2021-12-07","arxiv_id":"2112.03951","repositories_listed":0,"syntology":null},{"url":null,"slug":"shrub-ensembles-for-online-classification","title":"Shrub Ensembles for Online Classification","date":"2021-12-07","arxiv_id":"2112.03723","repositories_listed":0,"syntology":null},{"url":null,"slug":"unfairness-despite-awareness-group-fair","title":"Unfairness Despite Awareness: Group-Fair Classification with Strategic Agents","date":"2021-12-06","arxiv_id":"2112.02746","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-for-radio-astronomy","title":"Quantum Machine Learning for Radio Astronomy","date":"2021-12-05","arxiv_id":"2112.02655","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-real-world-pathological-voice","title":"Toward Real-World Voice Disorder Classification","date":"2021-12-05","arxiv_id":"2112.02538","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-label-thresholding-methods-for","title":"Adaptive label thresholding methods for online multi-label classification","date":"2021-12-04","arxiv_id":"2112.02301","repositories_listed":0,"syntology":null},{"url":null,"slug":"multilingual-text-classification-for","title":"Multilingual Text Classification for Dravidian Languages","date":"2021-12-03","arxiv_id":"2112.01705","repositories_listed":0,"syntology":null},{"url":null,"slug":"vision-pair-learning-an-efficient-training","title":"Vision Pair Learning: An Efficient Training Framework for Image Classification","date":"2021-12-02","arxiv_id":"2112.00965","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-online-passive-aggressive-algorithm-for","title":"An online passive-aggressive algorithm for difference-of-squares classification","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"asymmetric-error-control-under-imperfect","title":"Asymmetric error control under imperfect supervision: a label-noise-adjusted Neyman-Pearson umbrella algorithm","date":"2021-12-01","arxiv_id":"2112.00314","repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-shallow-and-deep-representations","title":"Combining Shallow and Deep Representations for Text-Pair Classification","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"comma-icon-multilingual-gender-biased-and","title":"ComMA@ICON: Multilingual Gender Biased and Communal Language Identification Task at ICON-2021","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-learning-of-global-and-local-2","title":"Contrastive Learning of Global and Local Video Representations","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-active-learning-for-gaussian","title":"Efficient Active Learning for Gaussian Process Classification by Error Reduction","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-sparse-pca-method-for-face-and-image","title":"Improved sparse PCA method for face and image recognition","date":"2021-12-01","arxiv_id":"2112.00207","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-gaussian-mixtures-with-generalized","title":"Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-fusion-for-improving-mammography","title":"Multi-task fusion for improving mammography screening data classification","date":"2021-12-01","arxiv_id":"2112.01320","repositories_listed":0,"syntology":null},{"url":null,"slug":"re-ranking-for-image-retrieval-and","title":"Re-ranking for image retrieval and transductive few-shot classification","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"see-more-for-scene-pairwise-consistency","title":"See More for Scene: Pairwise Consistency Learning for Scene Classification","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"structure-aware-label-smoothing-for-graph","title":"Structure-Aware Label Smoothing for Graph Neural Networks","date":"2021-12-01","arxiv_id":"2112.00499","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-experimentally-robust-and","title":"Training Experimentally Robust and Interpretable Binarized Regression Models Using Mixed-Integer Programming","date":"2021-12-01","arxiv_id":"2112.00434","repositories_listed":0,"syntology":null}],"record_sha256":"b7cb2bf08ea10afce5592ae47a7df1a888831c7593ad1b3b1378138506994027","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}